Microarchitectural analysis of a GPU implementation of the most apparent distortion image quality assessment algorithm

Vignesh Kannan, Joshua Holloway, Sohum Sohoni, Damon M. Chandler

Research output: Contribution to journalConference article

2 Scopus citations

Abstract

Due to the massive popularity of digital images and videos over the past several decades, the need for automated quality assessment (QA) is greater than ever. Accordingly, the impetus on QA research has focused on improving prediction accuracy. However, for many application areas, such as consumer electronics, the runtime performance and related computational considerations are equally as important as the accuracy. Most modern QA algorithms exhibit a large computational complexity. However, the large complexity of these algorithms does not necessarily prohibit their ability of achieving low runtimes if hardware resources are used appropriately. GPUs, which offer a large amount of parallelism and a specialized memory hierarchy, should be well-suited for QA algorithm deployment.

Original languageEnglish (US)
Pages (from-to)36-41
Number of pages6
JournalIS and T International Symposium on Electronic Imaging Science and Technology
DOIs
StatePublished - Jan 1 2017
EventImage Quality and System Performance XIV, IQSP 2017 - Burlingame, United States
Duration: Jan 29 2017Feb 2 2017

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Human-Computer Interaction
  • Software
  • Electrical and Electronic Engineering
  • Atomic and Molecular Physics, and Optics

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